Secondary DNA transfer on denim using a human blood analogue

DNA quantification technology has increased in accuracy and sensitivity, now allowing for detection and profiling of trace DNA. Secondary DNA transfer occurs when DNA is deposited via an intermediary source (e.g. clothing, tools, utensils). Multiple courtrooms have now seen secondary transfer introduced as an explanation for DNA being present at a crime scene, but sparse experimental studies mean expert opinions are often limited. Here, we used bovine blood and indigo denim substrates to quantify the amount of secondary DNA transfer and quality of STRs under three different physical contact scenarios: passive, pressure, and friction. We showed that the DNA transfer was highest under a friction scenario, followed by pressure and passive treatments. The STR profiles showed a similar, albeit less pronounced trend, with correctly scored alleles and genotype completeness being highest under a friction scenario, followed by pressure and passive. DNA on the primary substrate showed a decrease in concentration and genotype completeness both immediately and at 24 hours, suggestive of a loss of DNA during the primary transfer. The majority of secondary transfer samples amplified less than 50% of STR loci regardless of contact type. This study showed that while DNA transfer is common between denim, this is not manifested in full STR profiles. We discuss the possible technical solutions to partial profiles from trace DNA, and more broadly the ubiquity of secondary DNA transfer.

Primary admission and secondary transfer of trauma patients to Dutch level I and level II trauma centers: predictors and outcomes

Purpose The importance and impact of determining which trauma patients need to be transferred between hospitals, especially considering prehospital triage systems, is evident. The objective of this study was to investigate the association between mortality and primary admission and secondary transfer of patients to level I and II trauma centers, and to identify predictors of primary and secondary admission to a designated level I trauma center. Methods Data from the Dutch Trauma Registry South West (DTR SW) was obtained. Patients ≥ 18 years who were admitted to a level I or level II trauma center were included. Patients with isolated burn injuries were excluded. In-hospital mortality was compared between patients that were primarily admitted to a level I trauma center, patients that were transferred to a level I trauma center, and patients that were primarily admitted to level II trauma centers. Logistic regression models were used to adjust for potential confounders. A subgroup analysis was done including major trauma (MT) patients (ISS > 15). Predictors determining whether patients were primarily admitted to level I or level II trauma centers or transferred to a level I trauma center were identified using logistic regression models. Results A total of 17,035 patients were included. Patients admitted primarily to a level I center, did not differ significantly in mortality from patients admitted primarily to level II trauma centers (Odds Ratio (OR): 0.73; 95% confidence interval (CI) 0.51–1.06) and patients transferred to level I centers (OR: 0.99; 95%CI 0.57–1.71). Subgroup analyses confirmed these findings for MT patients. Adjusted logistic regression analyses showed that age (OR: 0.96; 95%CI 0.94–0.97), GCS (OR: 0.81; 95%CI 0.77–0.86), AIS head (OR: 2.30; 95%CI 2.07–2.55), AIS neck (OR: 1.74; 95%CI 1.27–2.45) and AIS spine (OR: 3.22; 95%CI 2.87–3.61) are associated with increased odds of transfers to a level I trauma center. Conclusions This retrospective study showed no differences in in-hospital mortality between general trauma patients admitted primarily and secondarily to level I trauma centers. The most prominent predictors regarding transfer of trauma patients were age and neurotrauma. These findings could have practical implications regarding the triage protocols currently used.

A New Classification Method in Ultrasound Images of Benign and Malignant Thyroid Nodules Based on Transfer Learning and Deep Convolutional Neural Network

Thyroid nodule is a clinical disorder with a high incidence rate, with large number of cases being detected every year globally. Early analysis of a benign or malignant thyroid nodule using ultrasound imaging is of great importance in the diagnosis of thyroid cancer. Although the b-mode ultrasound can be used to find the presence of a nodule in the thyroid, there is no existing method for an accurate and automatic diagnosis of the ultrasound image. In this pursuit, the present study envisaged the development of an ultrasound diagnosis method for the accurate and efficient identification of thyroid nodules, based on transfer learning and deep convolutional neural network. Initially, the Total Variation- (TV-) based self-adaptive image restoration method was adopted to preprocess the thyroid ultrasound image and remove the boarder and marks. With data augmentation as a training set, transfer learning with the trained GoogLeNet convolutional neural network was performed to extract image features. Finally, joint training and secondary transfer learning were performed to improve the classification accuracy, based on the thyroid images from open source data sets and the thyroid images collected from local hospitals. The GoogLeNet model was established for the experiments on thyroid ultrasound image data sets. Compared with the network established with LeNet5, VGG16, GoogLeNet, and GoogLeNet (Improved), the results showed that using GoogLeNet (Improved) model enhanced the accuracy for the nodule classification. The joint training of different data sets and the secondary transfer learning further improved its accuracy. The results of experiments on the medical image data sets of various types of diseased and normal thyroids showed that the accuracy rate of classification and diagnosis of this method was 96.04%, with a significant clinical application value.

Contact transfer of engineered nanomaterials in the workplace

This study investigates the potential spread of cadmium selenide quantum dots in laboratory environments through contact of gloves with simulated dry spills on laboratory countertops. Secondary transfer of quantum dots from the contaminated gloves to other substrates was initiated by contact of the gloves with different materials found in the laboratory. Transfer of quantum dots to these substrates was qualitatively evaluated by inspection under ultraviolet illumination. This secondary contact resulted in the delivery of quantum dots to all the evaluated substrates. The amount of quantum dots transferred was quantified by elemental analysis. The residue containing quantum dots picked up by the glove was transferred to at least seven additional sections of the pristine substrate through a series of sequential contacts. These results demonstrate the potential for contact transfer as a pathway for spreading nanomaterials throughout the workplace, and that 7-day-old dried spills are susceptible to the propagation of nanomaterials by contact transfer. As research and commercialization of engineered nanomaterials increase worldwide, it is necessary to establish safe practices to protect workers from the potential for chronic exposure to potentially hazardous materials. Similar experimental procedures to those described herein can be adopted by industries or regulatory agencies to guide the development of their nanomaterial safety programmes.

RFU derived LRs for activity level assignments using Bayesian Networks

A comparative study has been carried out, comparing two different methods to calculate activity level likelihood ratios (LRa) using Bayesian Networks. The first method uses the sub-source likelihood ratio (log10LRφ) as a 'quality indicator'. However, this has been criticised as introducing potential bias from population differences in allelic proportions. An alternative method has been introduced that is based upon the total RFU of a DNA profile that is adjusted, by multiplication, of the mixture proportion (Mx) which is calculated from quantitative probabilistic genotyping software (EuroForMix). Bayesian logistic regressions of direct transfer data showed that the two methods were comparable. Differences were attributed to sampling error, and small sample sizes of secondary transfer data. The Bayesian approach facilitates comparative studies by taking account of sampling error; it can easily be extended to compare different methods.

Inter-hospital transfer of polytrauma and severe traumatic brain injury patients: Retrospective nationwide cohort study using data from the Swiss Trauma Register

Introduction Polytrauma and traumatic brain injury (TBI) patients are among the most vulnerable patients in trauma care and exhibit increased morbidity and mortality. Timely care is essential for their outcome. Severe TBI with initially high scores on the Glasgow Coma (GCS) scores is difficult to recognise on scene and referral to a Major Trauma Center (MTC) might be delayed. Therefore, we examined current referral practice, injury patterns and mortality in these patients. Materials and methods Retrospective, nationwide cohort study with Swiss Trauma Register (STR) data between 01/012015 and 31/12/2018. STR includes patients ≥16 years with an Injury Severity Score (ISS) >15 and/or an Abbreviated Injury Scale (AIS) for head >2. We performed Cox proportional hazard models with injury type as the primary outcome and mortality as the dependent variable. Secondary outcomes were inter-hospital transfer and age. Results 9,595 patients were included. Mortality was 12%. 2,800 patients suffered from isolated TBI. 69% were men. Median age was 61 years and median ISS 21. Two thirds of TBI patients had a GCS of 13–15 on admission to the Emergency Department (ED). 26% of patients were secondarily transferred to an MTC. Patients with isolated TBI and those aged ≥65 years were transferred more often. Crude analysis showed a significantly elevated hazard for death of 1.48 (95%CI 1.28–1.70) for polytrauma patients with severe TBI and a hazard ratio (HR) of 1.82 (95%CI 1.58–2.09) for isolated severe TBI, compared to polytrauma patients without TBI. Patients directly admitted to the MTC had a significantly elevated HR for death of 1.63 (95%CI 1.40–1.89), compared to those with secondary transfer. Conclusions A high initial GCS does not exclude the presence of severe TBI and triage to an MTC should be seriously considered for elderly TBI patients.

Implementing the NHS England Long Term Plan for stroke: how should reperfusion services be configured? A modelling study

Objectives: To guide policy when planning reperfusion thrombolysis (IVT) and thrombectomy (MT) services for acute stroke in England, focussing on the choice between ‘mothership’ (direct conveyance to an MT centre) and ‘drip-and-ship' (secondary transfer for MT after local IVT) provision and the impact of bypassing local acute stroke centres.Methods: Computer modelling was used to estimate the likely outcomes from reperfusion therapies, along with admission numbers to units, based on expected times to IVT and MT.Results: Without pre-hospital selection for LAO, 94% of the population of England live in areas where the greatest clinical benefit accrues from direct conveyance to an IVT/MT centre. If this model was followed then net benefit from reperfusion is predicted to be increased from 31 to 34 additional disability-free outcomes / 1,000 admissions. However, this policy produces unsustainable admission numbers at these centres, and depletes all but 19 IVT-only units of all stroke admissions. Implementing a maximum permitted additional travel time to bypass an IVT-only unit, or using a pre-hospital test for LAO, both increase net benefit over the current drip-and-ship model, but produce a similar destabilising effect on acute systems of care. Use of IVT-only units manage admission numbers to IVT/MT centres.Conclusions: The mothership model reduces time to MT at the cost of increased time to IVT, but the benefit of faster MT is predicted to lead to a modest improvement in overall outcomes. Providing a sustainable national system of acute stroke care requires a hybrid of mothership and drip-and-ship provision.

The “Flying Intervention Team”: A Novel Stroke Care Concept for Rural Areas

<b><i>Background:</i></b> Endovascular treatment of large vessel occlusion in acute ischemic stroke patients is difficult to establish in remote areas, and time dependency of treatment effect increases the urge to develop health care concepts for this population. <b><i>Summary:</i></b> Current strategies include direct transportation of patients to a comprehensive stroke center (CSC) (“mothership model”) or transportation to the nearest primary stroke center (PSC) and secondary transfer to the CSC (“drip-and-ship model”). Both have disadvantages. We propose the model “flying intervention team.” Patients will be transported to the nearest PSC; if telemedically identified as eligible for thrombectomy, an intervention team will be acutely transported via helicopter to the PSC and endovascular treatment will be performed on site. Patients stay at the PSC for further stroke unit care. This model was implemented at a telestroke network in Germany. Fifteen remote hospitals participated in the project, covering 14,000 km² and a population of 2 million. All have well established telemedically supported stroke units, an angiography suite, and a helicopter pad. Processes were defined individually for each hospital and training sessions were implemented for all stroke teams. An exclusive project helicopter was installed to be available from 8 a.m. to 10 p.m. during 26 weeks per year. <b><i>Key Messages:</i></b> The model of the flying intervention team is likely to reduce time delays since processes will be performed in parallel, rather than consecutively, and since it is quicker to move a medical team rather than a patient. This project is currently under evaluation (clinicaltrials NCT04270513).